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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.21

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-02-10, 12:44 CET based on data in: /cfs/klemming/projects/supr/naiss2023-23-542/VR/SA_workshop/QC


        General Statistics

        Showing 145/145 rows and 10/13 columns.
        Sample NameN50 (Kbp)Assembly Length (Mbp)% Salmonella enterica% Top 5 Species% Salmonella enterica% Top 5 Species% Unclassified% Dups% GCM Seqs
        100N
        264.8Kbp
        4.7Mbp
        100N_1
        53.7%
        51%
        4.4M
        100N_2
        52.7%
        51%
        4.4M
        100N_kraken_report
        85.4%
        91.7%
        101N
        268.3Kbp
        4.8Mbp
        101N_1
        32.7%
        51%
        4.2M
        101N_2
        29.4%
        51%
        4.2M
        101N_kraken_report
        85.0%
        87.5%
        23
        271.1Kbp
        4.9Mbp
        23_1
        54.8%
        50%
        3.4M
        23_2
        51.6%
        50%
        3.4M
        23_kraken_report
        81.4%
        90.7%
        256
        219.3Kbp
        4.8Mbp
        256_1
        43.8%
        52%
        1.6M
        256_2
        42.5%
        51%
        1.6M
        256_kraken_report
        89.1%
        90.6%
        263
        180.0Kbp
        4.9Mbp
        263_1
        50.5%
        51%
        3.8M
        263_2
        47.9%
        51%
        3.8M
        263_kraken_report
        94.1%
        98.0%
        264
        268.3Kbp
        4.8Mbp
        264_1
        36.9%
        51%
        2.9M
        264_2
        34.9%
        51%
        2.9M
        264_kraken_report
        82.9%
        87.8%
        282
        254.4Kbp
        5.0Mbp
        282_1
        39.5%
        52%
        5.3M
        282_2
        36.8%
        52%
        5.3M
        282_kraken_report
        67.2%
        82.8%
        290
        268.3Kbp
        4.8Mbp
        290_1
        40.4%
        51%
        4.3M
        290_2
        38.1%
        51%
        4.3M
        290_kraken_report
        80.0%
        86.7%
        291
        270.7Kbp
        4.8Mbp
        291_1
        46.9%
        52%
        3.8M
        291_2
        44.5%
        52%
        3.8M
        291_kraken_report
        85.7%
        88.1%
        292
        268.3Kbp
        4.8Mbp
        292_1
        25.0%
        51%
        2.8M
        292_2
        24.3%
        51%
        2.8M
        292_kraken_report
        80.0%
        86.7%
        296
        268.3Kbp
        4.8Mbp
        296_1
        26.8%
        51%
        1.4M
        296_2
        26.9%
        51%
        1.4M
        296_kraken_report
        80.0%
        86.7%
        297
        268.3Kbp
        4.8Mbp
        297_1
        39.7%
        51%
        3.9M
        297_2
        37.9%
        51%
        3.9M
        297_kraken_report
        76.1%
        84.8%
        298
        270.7Kbp
        4.8Mbp
        298_1
        42.9%
        51%
        2.7M
        298_2
        42.6%
        51%
        2.7M
        298_kraken_report
        79.5%
        86.4%
        30
        270.9Kbp
        4.9Mbp
        300
        269.6Kbp
        4.8Mbp
        300_1
        41.0%
        51%
        5.2M
        300_2
        41.7%
        51%
        5.2M
        300_kraken_report
        80.0%
        87.5%
        304
        255.3Kbp
        4.8Mbp
        304_1
        32.3%
        51%
        1.6M
        304_2
        32.1%
        51%
        1.6M
        304_kraken_report
        81.4%
        86.0%
        306
        268.3Kbp
        4.8Mbp
        306_1
        46.5%
        51%
        4.8M
        306_2
        46.6%
        51%
        4.8M
        306_kraken_report
        76.7%
        81.4%
        308
        268.3Kbp
        4.7Mbp
        308_1
        29.8%
        51%
        2.5M
        308_2
        30.1%
        51%
        2.5M
        308_kraken_report
        83.8%
        89.2%
        30_1
        34.2%
        52%
        8.2M
        30_2
        35.5%
        52%
        8.2M
        30_kraken_report
        82.0%
        86.0%
        310
        270.7Kbp
        4.8Mbp
        310_1
        45.9%
        51%
        3.7M
        310_2
        46.1%
        51%
        3.7M
        310_kraken_report
        80.0%
        85.0%
        313
        230.7Kbp
        4.9Mbp
        313_1
        35.2%
        51%
        3.8M
        313_2
        32.1%
        51%
        3.8M
        313_kraken_report
        83.7%
        89.8%
        314
        270.8Kbp
        4.8Mbp
        314_1
        35.7%
        51%
        3.5M
        314_2
        35.0%
        51%
        3.5M
        314_kraken_report
        82.1%
        87.2%
        317
        268.3Kbp
        4.8Mbp
        317_1
        37.7%
        51%
        4.3M
        317_2
        36.4%
        51%
        4.3M
        317_kraken_report
        82.9%
        87.8%
        319
        253.8Kbp
        4.9Mbp
        319_1
        56.6%
        50%
        4.9M
        319_2
        56.4%
        50%
        4.9M
        319_kraken_report
        70.4%
        83.3%
        321
        320.1Kbp
        4.8Mbp
        321_1
        18.7%
        52%
        3.5M
        321_2
        17.6%
        52%
        3.5M
        321_kraken_report
        78.0%
        82.9%
        43
        270.7Kbp
        4.9Mbp
        43_1
        49.1%
        51%
        4.2M
        43_2
        48.8%
        51%
        4.2M
        43_kraken_report
        77.8%
        85.2%
        46
        225.4Kbp
        4.9Mbp
        46_1
        41.0%
        51%
        2.1M
        46_2
        39.3%
        51%
        2.1M
        46_kraken_report
        84.1%
        92.1%
        47
        219.3Kbp
        4.8Mbp
        47_1
        29.7%
        54%
        3.1M
        47_2
        26.7%
        54%
        3.1M
        47_kraken_report
        81.2%
        85.4%
        53
        313.7Kbp
        4.9Mbp
        53_1
        32.3%
        51%
        3.4M
        53_2
        31.6%
        51%
        3.4M
        53_kraken_report
        85.7%
        94.3%
        60
        219.3Kbp
        4.8Mbp
        60_1
        32.2%
        51%
        3.0M
        60_2
        33.1%
        51%
        3.0M
        60_kraken_report
        84.4%
        88.9%
        61
        254.0Kbp
        4.9Mbp
        61_1
        37.2%
        53%
        4.3M
        61_2
        36.5%
        53%
        4.3M
        61_kraken_report
        83.7%
        86.0%
        69
        220.6Kbp
        4.9Mbp
        69_1
        45.2%
        50%
        4.4M
        69_2
        45.5%
        50%
        4.4M
        69_kraken_report
        81.5%
        87.0%
        73
        84.3Kbp
        5.5Mbp
        73_1
        54.3%
        52%
        4.1M
        73_2
        44.9%
        52%
        4.1M
        73_kraken_report
        92.8%
        94.0%
        1.7%
        75
        199.0Kbp
        4.9Mbp
        75_1
        44.3%
        51%
        4.1M
        75_2
        44.3%
        51%
        4.1M
        75_kraken_report
        84.2%
        91.2%
        97N
        263.3Kbp
        4.9Mbp
        97N_1
        34.3%
        52%
        5.3M
        97N_2
        31.2%
        52%
        5.3M
        97N_kraken_report
        81.4%
        88.4%
        98N
        225.3Kbp
        4.9Mbp
        98N_1
        37.7%
        51%
        1.7M
        98N_2
        37.9%
        51%
        1.7M
        98N_kraken_report
        78.7%
        89.4%
        99N
        220.6Kbp
        4.9Mbp
        99N_1
        39.7%
        52%
        3.7M
        99N_2
        31.7%
        52%
        3.7M
        99N_kraken_report
        83.3%
        87.5%
        GCA_000486855.2_kraken_report
        100.0%
        100.0%

        QUAST

        QUAST is a quality assessment tool for genome assemblies, written by the Center for Algorithmic Biotechnology.DOI: 10.1093/bioinformatics/btt086.

        Assembly Statistics

        Showing 36/36 rows and 8/8 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)MisassembliesMismatches/100kbpIndels/100kbpGenome Fraction
        100N
        264.8Kbp
        0.0K
        693.4Kbp
        4.7Mbp
        9.0
        17.76
        1.40
        97.7%
        101N
        268.3Kbp
        0.0K
        694.1Kbp
        4.8Mbp
        7.0
        10.96
        1.09
        97.7%
        23
        271.1Kbp
        0.0K
        671.3Kbp
        4.9Mbp
        8.0
        10.90
        1.27
        97.7%
        256
        219.3Kbp
        0.0K
        550.6Kbp
        4.8Mbp
        6.0
        17.12
        1.32
        97.7%
        263
        180.0Kbp
        0.0K
        600.7Kbp
        4.9Mbp
        7.0
        17.80
        1.40
        97.8%
        264
        268.3Kbp
        0.0K
        693.0Kbp
        4.8Mbp
        6.0
        11.03
        1.09
        97.7%
        282
        254.4Kbp
        0.0K
        693.4Kbp
        5.0Mbp
        6.0
        14.38
        1.22
        97.8%
        290
        268.3Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        6.0
        11.16
        1.14
        97.7%
        291
        270.7Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        7.0
        11.06
        1.05
        97.7%
        292
        268.3Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        6.0
        11.10
        1.14
        97.7%
        296
        268.3Kbp
        0.0K
        693.4Kbp
        4.8Mbp
        6.0
        11.19
        1.09
        97.7%
        297
        268.3Kbp
        0.0K
        693.4Kbp
        4.8Mbp
        6.0
        11.03
        1.09
        97.7%
        298
        270.7Kbp
        0.0K
        646.0Kbp
        4.8Mbp
        9.0
        11.52
        1.16
        97.7%
        30
        270.9Kbp
        0.0K
        693.4Kbp
        4.9Mbp
        10.0
        19.09
        1.40
        97.9%
        300
        269.6Kbp
        0.0K
        693.4Kbp
        4.8Mbp
        6.0
        11.16
        1.09
        97.7%
        304
        255.3Kbp
        0.0K
        693.4Kbp
        4.8Mbp
        7.0
        10.96
        1.09
        97.7%
        306
        268.3Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        6.0
        11.34
        1.11
        97.8%
        308
        268.3Kbp
        0.0K
        647.2Kbp
        4.7Mbp
        7.0
        11.10
        1.14
        97.7%
        310
        270.7Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        6.0
        11.16
        1.14
        97.8%
        313
        230.7Kbp
        0.0K
        693.5Kbp
        4.9Mbp
        7.0
        21.54
        1.56
        97.9%
        314
        270.8Kbp
        0.0K
        693.3Kbp
        4.8Mbp
        7.0
        11.05
        1.07
        97.7%
        317
        268.3Kbp
        0.0K
        647.2Kbp
        4.8Mbp
        7.0
        11.09
        1.14
        97.8%
        319
        253.8Kbp
        0.0K
        659.5Kbp
        4.9Mbp
        5.0
        17.64
        1.22
        97.8%
        321
        320.1Kbp
        0.0K
        693.5Kbp
        4.8Mbp
        7.0
        22.33
        1.71
        97.9%
        43
        270.7Kbp
        0.0K
        646.9Kbp
        4.9Mbp
        7.0
        12.32
        1.23
        97.8%
        46
        225.4Kbp
        0.0K
        367.0Kbp
        4.9Mbp
        6.0
        17.17
        1.16
        97.8%
        47
        219.3Kbp
        0.0K
        597.1Kbp
        4.8Mbp
        5.0
        17.02
        1.69
        97.9%
        53
        313.7Kbp
        0.0K
        693.4Kbp
        4.9Mbp
        7.0
        17.96
        1.60
        97.9%
        60
        219.3Kbp
        0.0K
        557.5Kbp
        4.8Mbp
        5.0
        17.79
        1.38
        97.8%
        61
        254.0Kbp
        0.0K
        575.8Kbp
        4.9Mbp
        8.0
        11.69
        1.05
        97.8%
        69
        220.6Kbp
        0.0K
        597.3Kbp
        4.9Mbp
        5.0
        13.00
        1.60
        97.8%
        73
        84.3Kbp
        0.0K
        224.9Kbp
        5.5Mbp
        8.0
        56.81
        2.24
        97.8%
        75
        199.0Kbp
        0.0K
        725.0Kbp
        4.9Mbp
        5.0
        15.93
        1.09
        97.9%
        97N
        263.3Kbp
        0.0K
        693.4Kbp
        4.9Mbp
        10.0
        17.97
        1.36
        97.8%
        98N
        225.3Kbp
        0.0K
        659.5Kbp
        4.9Mbp
        6.0
        17.61
        1.22
        97.8%
        99N
        220.6Kbp
        0.0K
        597.3Kbp
        4.9Mbp
        6.0
        17.77
        1.34
        97.8%

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Bracken

        Bracken is a highly accurate statistical method that computes the abundance of species in DNA sequences from a metagenomics sample.DOI: 10.7717/peerj-cs.104.

        Top taxa

        The number of reads falling into the top 5 taxa across different ranks.

        To make this plot, the percentage of each sample assigned to a given taxa is summed across all samples. The counts for these top 5 taxa are then plotted for each of the 9 different taxa ranks. The unclassified count is always shown across all taxa ranks.

        The total number of reads is approximated by dividing the number of unclassified reads by the percentage of the library that they account for. Note that this is only an approximation, and that kraken percentages don't always add to exactly 100%.

        The category "Other" shows the difference between the above total read count and the sum of the read counts in the top 5 taxa shown + unclassified. This should cover all taxa not in the top 5, +/- any rounding errors.

        Note that any taxon that does not exactly fit a taxon rank (eg. - or G2) is ignored.

        Created with MultiQC

        Kraken

        Kraken is a taxonomic classification tool that uses exact k-mer matches to find the lowest common ancestor (LCA) of a given sequence.DOI: 10.1186/gb-2014-15-3-r46.

        Top taxa

        The number of reads falling into the top 5 taxa across different ranks.

        To make this plot, the percentage of each sample assigned to a given taxa is summed across all samples. The counts for these top 5 taxa are then plotted for each of the 9 different taxa ranks. The unclassified count is always shown across all taxa ranks.

        The total number of reads is approximated by dividing the number of unclassified reads by the percentage of the library that they account for. Note that this is only an approximation, and that kraken percentages don't always add to exactly 100%.

        The category "Other" shows the difference between the above total read count and the sum of the read counts in the top 5 taxa shown + unclassified. This should cover all taxa not in the top 5, +/- any rounding errors.

        Note that any taxon that does not exactly fit a taxon rank (eg. - or G2) is ignored.

        Created with MultiQC

        FastQC

        Version: 0.12.1

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Created with MultiQC

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        72 samples had less than 1% of reads made up of overrepresented sequences

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 1/1 rows and 3/3 columns.
        Overrepresented sequenceSamplesOccurrences% of all reads
        TACACTATCATCCTGATAGTGGCCCGCCGGAGGCATCGCAATGCGATCCC
        5
        37161
        0.0139%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Created with MultiQC

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        FastQC0.12.1